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Shutdown Risk Assessment of Small-Size Hydropower Station Under Typhoon Disaster
- Source :
- 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2).
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Most of the small-size hydropower stations are runoff hydropower stations and their output is determined by the upstream water supply. Consequently, the rainfall brought by typhoons will lead to the increment of runoff, increasing the output of small-size hydropower stations. The uncertain increment of the output of small-size hydropower stations will bring adverse effects on the security of power system, such as the voltage over-limit and the power overload of transmission lines. In this paper, a risk assessment method is proposed to assess the shutdown risk of small-size hydropower station under typhoon disaster. Firstly, Monte Carlo Method is employed to calculate the probabilistic load flow of power system with small-size hydropower station and the probability of node voltage over-limit and branch power overload is set to be the shutdown probability of small-size hydropower station. Secondly, the cost of load shedding which is optimized by Adaptive Particle Swarm optimization (APSO) algorithm is set to be the shutdown cost of small-size hydropower station. Finally, the IEEE-33 bus system is used to assess the shutdown risk of small-size hydropower station under typhoon disaster.
- Subjects :
- 0106 biological sciences
business.industry
010604 marine biology & hydrobiology
Shutdown
Node (networking)
Particle swarm optimization
02 engineering and technology
01 natural sciences
Electric power system
Electric power transmission
Typhoon
0202 electrical engineering, electronic engineering, information engineering
Environmental science
020201 artificial intelligence & image processing
business
Risk management
Hydropower
Marine engineering
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2)
- Accession number :
- edsair.doi...........012613ede30658466275deb2ec0c069d
- Full Text :
- https://doi.org/10.1109/ei250167.2020.9346841